1. Field of the Invention
The present invention relates to a multi-view video compression coding method and apparatus.
2. Description of the Related Art
“Multi-viewpoint image” means pictures shot at the same time by cameras located at different places. Also, “multi-view video” means time-continuation in these multi-viewpoint images. There is strong correlation between these multi-viewpoint images, except in the difference of the disparity. According to Japanese Patent Laid-Open No. 2005-260464, when these multi-viewpoint images are considered to be a series of pictures, it can be coded by using a motion compensation (a disparity compensation).
“Block matching” is a typical method in the disparity compensation between multi-viewpoint images. Detection of a disparity vector using “block matching” is carried out as follows.
The first camera shoots a first picture as a first viewpoint, and the second camera shoots a second picture as a second viewpoint. The first picture is split into small blocks. The first block in the first picture is moved in the second picture. And the second block having the highest similarity is searched for. Specifically, the first block and the second block minimize absolute error or squared error. Then, a distance between the second block and the first block is calculated as a disparity vector. A prediction error between the first block and the second block is coded, and the disparity vector is added to the coded data.
An object in the first picture is moved in the second picture, and the blocks are matched. That is to say, complete block matching is realized only when the surface of the object becomes vertical to the optical axes of the cameras.
However, when the surface of the object inclines to the optical axes of the cameras, the picture shot for that surface is different for each camera. That is to say, even if the first block of the first picture is moved in the second picture, it cannot search for the second block that is completely matched in the first block. That is because, the shape of the object in the first picture is different from the shape of the object in the second picture; they are projections.